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column position (one based) Possible fields: Y row row position (one based). If omitted, most recently encountered value is used. E expression expression for the cell K value value of the cell C column column reference R row row reference G defines shared value D defines shared expression S references shared value or shared expression N
A cell containing a formula, therefore, has two display components; the formula itself and the resulting value. The formula is normally only shown when the cell is selected by "clicking" the mouse over a particular cell; otherwise, it contains the result of the calculation. A formula assigns values to a cell or range of cells, and typically has ...
A graph can only contain a perfect matching when the graph has an even number of vertices. A near-perfect matching is one in which exactly one vertex is unmatched. Clearly, a graph can only contain a near-perfect matching when the graph has an odd number of vertices, and near-perfect matchings are maximum matchings. In the above figure, part (c ...
The case of exact graph matching is known as the graph isomorphism problem. [1] The problem of exact matching of a graph to a part of another graph is called subgraph isomorphism problem. Inexact graph matching refers to matching problems when exact matching is impossible, e.g., when the number of vertices in the two graphs are different. In ...
In statistics and related fields, a similarity measure or similarity function or similarity metric is a real-valued function that quantifies the similarity between two objects. Although no single definition of a similarity exists, usually such measures are in some sense the inverse of distance metrics : they take on large values for similar ...
Statistical inference can be made based on the Jaccard similarity index, and consequently related metrics. [6] Given two sample sets A and B with n attributes, a statistical test can be conducted to see if an overlap is statistically significant. The exact solution is available, although computation can be costly as n increases. [6]
INPUT: Graph G, matching M on G OUTPUT: augmenting path P in G or empty path if none found B01 function find_augmenting_path(G, M) : P B02 F ← empty forest B03 unmark all vertices and edges in G, mark all edges of M B05 for each exposed vertex v do B06 create a singleton tree { v} and add the tree to F B07 end for B08 while there is an ...
In graph theory, a perfect matching in a graph is a matching that covers every vertex of the graph. More formally, given a graph G with edges E and vertices V, a perfect matching in G is a subset M of E, such that every vertex in V is adjacent to exactly one edge in M. The adjacency matrix of a perfect matching is a symmetric permutation matrix.